适合陕北枣区的良种选择研究

本文对陕北枣区现有的75个枣品种，选用13个性状指标。进行综合判别，初选出16个优良品种，其中制于品种6个、鲜食品种5个，兼用品种5个，结合陕北的气候特征和生产现状，主要研究了陕北良种的物候期、结实性状和果实品质。最终选出适合陕北栽培的优良（1）制干品种为中阳木枣、方木枣、猗头枣、赞皇大枣和骏枣；（2）鲜食品种为梨枣，牛奶脆枣、狗头枣；（3）加工蜜枣用的品种为扁圆团枣，赞皇大枣和方木枣。     

油茶优良无性系早期判别与分级的研究

油茶无性系更新造林水平的提高,最关键的问题是提高现有采穗圃中有关无性系穗条的遗传品质.为了简化常规判别油茶无性系优良度的方法,以及缩短判别的时间和提高判别效果,本文提出依据单株产量与每平方米冠幅产量,单株冠幅面积之间存在极显著的相关性因子来进行判别分级,并依此建立判别数学模型,以满足当前油茶生产发展的需要。与常规鉴定方法进行了比较验证,效果极佳,可以用于实际生产.     

滇中地区森林火险等级的判别分析

森林火险等级预报，目前国外使用的方法一般为概率论与数理统计的方法，本文用多元统计中的“主成分分析”方法挑选判别因子，在此基础上用“判别分析”中的不同方法对所抽取的样品进行判别，通过对不同判别方法所得结果的比较，探索以多元统计分析为数学工具作林火预报的方法。     

木工机床振动薄弱环节的模糊识别方法

在模糊综合评判理论基础上，首先建立起木工机床在相同评价集上的薄弱环节判别模型，给出不同判别原则下的模糊运算模型，在模糊综合判别模型的基础上，讨论了不同层次和不同侧面判别的综合问题，提出了模糊综合判别算法，依据该方法可实现对多子结构复杂木工机床薄弱环节的识别。     

锥栗人工林营养综合指标诊断研究

在叶片中5种主要养分元素测定和分析的基础上,首次应用判别分析法建立了综合指标诊断判别系统,对不同产量类型的锥栗人工林营养进行了判别诊断分析.当将产量水平划分为2类时,采用1维判别分析进行回判,不同的分类方法可得到不同的正判率,高产类及(中产+低产)类的划分所得到的正判率均为100%;而(高产+中产)类及低产类的划分所得到的正判率分别为88.33%和86.67%.将产量划分为高、中、低3类的情况下,用1维判别进行回判的结果其正判率分别是100%、86.70%和83.33%;用2维判别进行回判,则正判率分别为100%、100%和83.33%.因此,类别的划分及判别函数的维数是影响判别诊断分析效果的重要因子.     

滇中地区森林火险等级的判别分析

森林火险等级预报,目前国外使用的方法一般为概率论与数理统计的方法。本文用多元统计中的“主成分分析”方法挑选判别因子,在此基础上用“判别分析”中的不同方法对所抽取的样品进行判别,通过对不同判别方法所得结果的比较,探索以多元统计分析为数学工具作林火预报的方法。     

近红外光谱结合回归分析预测法判别木材的生物腐朽

利用近红外光谱结合多变量回归分析中常用的主成分回归(PCR)和偏最小二乘法回归(PLSR)分析预测法来判别木材的生物腐朽,并与前期采用的SIMCA和PLS-DA 2种判别方法进行对比分析.结果表明:1)应用近红外光谱结合多变量回归分析方法对校正集样本建立的判别模型,其校正及验证结果与标准值的相关性很高,相关系数均大于0.95,SEC和SEP都很低(0.07 ～0.20),利用模型对未参与建模的样本进行检测,发现2个模型对未腐朽、白腐和褐腐3种类型样本的判别准确率均为100％(偏差都小于0.27);2)对于相同样本集的判别效果,PLSR法比PCR法的判别效果好,且二者都比采用SIMCA法的效果好,并都与PLS-DA法的判别结果相近,说明利用近红外光谱结合回归分析预测法能有效地检测木材的生物腐朽,并对生物腐朽的类型进行准确判别.     

沙松的优树选择

采用优势度和判别分析相结合的方法 ,对东京城林业局大沟林场 8株复选沙松优树进行了判断 ,同时对 30株沙松初选优树进行了二级判别分析 ,并建立了判别函数。提出了沙松优树选择的原则、标准及优树复选的标准 ,同时例举了判别法的具体应用实例     

刚性与刚弹性方案的简明判别

运用等刚度原则，推导出横墙不符合《砌体结构设计规范》要求时，刚性、刚弹性方案的简明判别公式，适用于混合结构房屋静力计算方案的简明判别。     

鱼中毒与泛塘判别与解救

养鱼池塘,往往因管理上的疏忽而发生塘鱼中毒或泛塘事故,因此,准确地判别中毒与泛塘,并及时采取相应的解救措施,减轻损失,是渔业生产上一项重要的技术工作。一般可从几方面进行判别和解救。     

Application of near-infrared spectroscopy to wood discrimination

 This study deals with a new nondestructive discriminant analysis by which wood can be classified on the basis of a combination of near-infrared (NIR) spectroscopy and Mahalanobis' generalized distance. Its accuracy and reasonability were examined for wood samples with various moisture contents ranging from oven-dried to a fully saturated free water state. In a discriminant analysis employing second derivative spectra, each wood group was well distinguished. Mahalanobis' generalized distances between softwoods are relatively independent of analytical pattern, whereas the distances between hardwoods are large for easy classification. There may be two reasons for selecting a wavelength: (1) when the chemical component of wood substance relates to the discriminant analysis; and (2) when the difference in moisture content with wood species relates to them. When we correctly construct the database of NIR spectra, confirming the purpose of the analysis, suitable wood discrimination should be possible. Received: January 23, 2002 / Accepted: March 15, 2002 Acknowledgment The authors sincerely thank the Tanabe Southeast Asia Nations Friendship Foundation for financial support. Part of this report was presented at the 51nd Annual Meeting of the Japan Wood Research Society, 2001 Correspondence to:S. Tsuchikawa     

基于多元素含量的统计学方法鉴别我国不同产地核桃

[目的]对我国不同产地核桃进行鉴别,为核桃的原产地保护提供一定的基础数据和理论依据。[方法]应用电感耦合等离子体质谱(ICP-MS)测定全国8个核桃主产省128份核桃样品中35种元素含量,结合单因素方差分析、主成分分析(PCA)和线性判别分析(LDA),建立判别模型,对核桃产地进行鉴别。[结果]表明:核桃中主要微量营养元素为Fe、Zn、Cu和Ni等,重金属(Pb、Cd和As)及稀土元素含量较低;单因素方差分析结果表明,不同地区核桃样品中元素组成差异显著(P0.05);主成分分析表明,不同地区核桃样品中的特征元素为稀土元素以及Co、Fe、Rb、Zn、Tl、Cu、Cd、Ba、Sm、Sc、Mo和Ti等元素;应用线性判别分析建立了不同产地核桃判别模型,8个省份核桃整体判别正确率为99.2%,同时,应用线性判别分析建立了核桃地理标志产品与非地理标志产品判别模型,6种核桃地理标志与非地理标志产品整体判别正确率为95.7%。[结论]通过测定核桃中多种元素含量,结合主成分分析(PCA)和线性判别分析(LDA)等方法,可对不同产地核桃进行鉴别。     

Classification of defects in cork planks using image analysis

Summary Image analysis techniques were used on cork surfaces of transverse sections of planks and multivariate analysis was applied to differentiate pores (lenticular channels) from important defects such as nail (horizontal and vertical) and insect galeries. The discriminant analysis showed that the variables area, perimeter, specific length and width, diameters in the radial and in the tangential direction, as well as the optical density could be combined in three discriminant functions that could make the classification. Defect specific classification functions gave good results for the automatic classification of pores, insect galeries and horizontal nail (error <10%), and acceptable for vertical nail (20% error).     

森林生态系统类型自然保护区功能区划探讨

分析了我国目前在保护区功能区划技术方面存在的问题。针对森林生态系统类型自然保护区,提出以森林小班为基本区划单元、完善判别分析指标体系、提高相关利益群体参与性的功能区划分思路。     

苦楝表型区划的研究

在对苦楝24个群体729个个体18个表型性状指标测定的基础上,根据主成分分析和聚类分析结果,将苦楝中国分布区区划为5大表型区10个亚区.对表型区划结果进行典型判别分析发现,苦楝各表型区间家系性状分化比较明显,而各表型区内家系分化不明显.对苦楝5大表型区区划的合理性进行了回判预测,有93.8%回判正确.     

Aeciospores of Cronartium flaccidum,C. ribicola and Endocronartium pini show no differences in morphology

The morphology of the aeciospores of the pine stem rust fungi Cronartium flaccidum, Cronartium ribicola and Endocronartium pini, collected from nine locations in Finland, Sweden and Italy, was compared. Surface structures of 900 aeciospores were visually classified using a scanning electron microscope, and dimensions of 1100 aeciospores were measured from micrographs. The data grouping was tested with discriminant analysis. The spores had well-defined smooth areas and annulate warts on their surface. E. pini, C. flaccidum and C. ribicola could not be distinguished by the surface structures of the spores. The grouping of spores by dimensions into sample locations was statistically significant by one discriminant function, while the grouping into species was not. The observed similarities corroborated the current views on the close relationship of C. flaccidum and E. pini.     

Site classification for Maiden's gum, Eucalyptus globulus subsp. Maidenii, in Rwanda

Soil A horizon and meteorological variables were used to derive a site index prediction equation and a site class discriminant rule for Maiden's gum planted in Rwanda. Quadratic discriminant analysis supplied a higher site class prediction accuracy from less variables than site index prediction equation. The most important discriminatory variables were P concentration, Mg stores, clay-plus-silt fraction, Al concentration, December rainfall, and Mn : Ca ratio.     

Pattern recognition as a tool to discriminate softwood and hardwood bark fractions with different particle size

The aim of this study was to characterize the chemical composition of different granulometric fractions obtained by milling of the bark of two softwood [Norway spruce, Picea abies (L.) Karst., and Scots pine, Pinus sylvestris L.] and two hardwood species (birch, Betula pendula Roth, and eucalypt, Eucalyptus globulus Labill.), and to discriminate between them on the basis of their chemical composition content via pattern recognition techniques [principal component analysis (PCA), cluster analysis (CA), and discriminant analysis (DA)]. Bark chemical composition differed between species, and chemical variables could be used to differentiate between them. Size reduction yields granulometric fractions that are not chemically homogeneous and that can also be discriminated. Therefore, potential applications of bark in valorization programs have to carefully consider the species-specific composition and their size reduction patterns. PCA and CA were adequate tools to characterize the different bark fractions within each species. DA allowed identifying the bark samples according to species and independently from particle size. Pattern recognition statistical methods were shown to be useful tools to analyse bark fractions and chemically discriminate species and fractions.     

Classification of the hot air heat treatment degree of larch wood using a multivariate analysis of near-infrared spectroscopy

In this study, hot air heat treatments of larch (Larix kaempferi) wood specimens were conducted at various temperatures (160–220 °C) and times (1–12 h) to classify the degree of hot air heat treatment using near-infrared (NIR) spectroscopy. NIR reflectance spectra were acquired from specimen cross-sections and were then preprocessed using the standard normal variate. Hierarchical clustering analysis (HCA) using the complete linkage and squared Euclidean distance was conducted to classify the three degrees of heat treatment. A principal component score plot of the NIR spectra was well grouped by the HCA grouping result, and the first component reflected the cluster analysis grouping well. A partial least squares discriminant analysis was performed to develop the discriminant regression model of the three heat treatment degrees. The R² and root mean square error of validation were 0.959 and 0.191, respectively. NIR is considered to be a good candidate to routinely measure the degree of hot air treatment for larch wood.     

多回波机载LiDAR数据提取林地DEM的判别分析方法

选取包含明显空地的林地作为建模样地,通过对其激光点云单次和多次回波数据的三维空间坐标分布、反射强度分布和垂直分布3方面特征进行探讨,进而提出基于判别分析的林地DEM提取方法.取林木郁闭并实测了大量(1 472个)地面控制点的验证样地加以检验.结果表明:对山区林地林木复杂环境的DEM提取采用判别分析的方法是可行的,其精度达到高差总平均值0.24 m,方差0.05,高差处于-0.5～0.5 m之间的数据占总量的93.85％;与直接的网格窗口划分DEM滤波模拟对照比较,其结果较优.